Polymer engineering involves making mutations (atomic replacement, insertion, or deletion) to a polymer of known sequence and structure, and evaluating the effects of such mutations on the physical and biological properties of the polymer. Because of the enormous resources involved in both making such mutations and testing the effects of such mutations, efforts are directed to in silico testing as a means of limiting the number of mutations that are actually synthesized and tested in the laboratory. An example of one such approach is the systems and methods for estimating the difference in conformational flexibility between the native polymer and the derivation of the polymer (where the derivation of the polymer has the mutation) in the region near the site of the mutation that are provided in U.S. Patent Application No. 61/793,203, entitled “Systems and Methods for Identifying Thermodynamic Effects of Atomic Changes to Polymers,” filed Mar. 15, 2013, which is hereby incorporated by reference herein in its entirety.
In silico testing of polymers requires substantial computing power to take into account the conformational flexibility of these polymers. Moreover, each polymer and each mutation requires much customized study, and appropriate methods for evaluating mutations are still undergoing development. Because of the need for customized study and because of the ongoing research into appropriate methods for studying polymers in silico, there are multiple applications that are invoked, often on a repeatable basis in any modeling project.
Given the above-background, what is needed are systems and methods for putting these multiple applications together in different ways (e.g., workflow), and experimenting with these different workflows. For instance, such systems and methods are needed to address questions such as whether (i) a workflow that involves running application A before application B, and then following it up with application C produces a better output than (ii) a workflow that takes the average of ten instances of application A and ten instances of application B followed by application C. Another example of the type of question for which better systems and methods are needed is the determination of whether better protein modeling is achieved by substituting out application B in a workflow for a different algorithm completely, perhaps application Z, which does the same thing as application B but has completely different internal workings.